The Composition Forecasting Research for Cupola Melting Process

Jian Xin Zhou; Liang Sun; Zhen Zhong Shi; Hong Wang

doi:10.4028/www.scientific.net/AMM.217-219.1636

Paper Titles

Research Progress of Methods to Improve Fatigue Strength of Welded Structures
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Finite Element Mesh Model Analysis and Model Information Transform Method in Casting Simulation Process
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Finite Element Numerical Simulation of Tubing Premium Connection
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Surface Roughness Predictive Model of UNS A97075 Aluminum Pieces Obtained by Dry Turning Tests Based on the Cutting Forces
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The Composition Forecasting Research for Cupola Melting Process
p.1636

Study of the Machining Principle and Influencing of ELID Grinding on SiC
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Simulation and Experimental Analysis of Moulding Processes of Glass Diffractive Optical Elements
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Preliminary Study on the Rotational Indexing Machining Technology of Straight Bevel Gear
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Rebound Deformation of Thin Part Caused by Clamping Force in End Milling
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 217-219The Composition Forecasting Research for Cupola...

The Composition Forecasting Research for Cupola Melting Process

Abstract:

This paper summarizes components and phases involved in the cupola melting process, then brings out a composition forecasting model based on the minimum Gibbs energy principle and the equilibria calculation algorithms of multiphase and multicomponent. Besides, the relationship between the melting parameters and the composition of molten iron is set up by using BP neural network based on the idea of indirect constraints. Finally, the paper probes the feasibility of the composition forecasting model with two examples. The application result shows that the prediction with this method can achieve strong practicability and popularization value.

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Periodical:

Applied Mechanics and Materials (Volumes 217-219)

Pages:

1636-1641

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.217-219.1636

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Online since:

November 2012

Authors:

Jian Xin Zhou, Liang Sun, Zhen Zhong Shi, Hong Wang

Keywords:

Composition Forecasting, Cupola, Genetic Algorithm (GA), Gibbs Free Energy Method, Melting

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